A Multi-Scenario Analysis of Urban Vitality Driven by Socio-Ecological Land Functions in Luohe, China

Xinyu Wang, Tian Bai, Yang Yang, Guifang Wang, Guohang Tian and László Kollányi ()
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Xinyu Wang: Institute of Landscape Architecture, Urban Planning and Garden Art, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary
Tian Bai: College of Landscape and Horticulture, Yunnan Agricultural University, Kunming 650201, China
Yang Yang: Institute of Landscape Architecture, Urban Planning and Garden Art, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary
Guifang Wang: Institute of Landscape Architecture, Urban Planning and Garden Art, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary
Guohang Tian: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
László Kollányi: Institute of Landscape Architecture, Urban Planning and Garden Art, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary

Land, 2024, vol. 13, issue 8, 1-22

Abstract: Urban Vitality (UV) is a critical indicator for measuring sustainable urban development and quality. It reflects the dynamic interactions and supply–demand coordination within urban systems, especially concerning the human–land relationship. This study aims to quantify the UV of Luohe City, China, for the year 2023, analyze its spatial characteristics, and investigate the driving patterns of socio-ecological land functions on UV intensity and heterogeneity under different scenarios. Utilizing multi-source data, including human mobility data from Baidu Location-Based Services (LBSs), Landsat-9, MODIS, and diverse geo-information datasets, we conducted factor screening and comprehensive assessments. Firstly, Self-Organizing Maps (SOMs) were employed to identify typical activity patterns, and the Urban Vitality Index (UVI) was calculated based on Human Mobility Intensity (HMI) data. Subsequently, a framework for quantity–quality–structure assessments weighted and aggregated sub-indicators to evaluate the Land Social Function (LSF) and Land Ecological Function (LEF). Following the screening process, a Multi-scale Geographically Weighted Regression (MGWR) was applied to analyze the scale and driving relationships between UVI and the land assessment sub-indicators. The results were as follows: (1) The UV distribution in Luohe City was highly uneven, with high vitality areas concentrated within the built-up regions. (2) UV showed significant correlations with both LSF and LEF. The influence of LSF on UV was stronger than that of LEF, with the effectiveness of LEF relying on the well-established provisioning of LSF. (3) Artificial Surface Ratio (ASR) and Corrected Night Lights (LERNCI) were identified as key drivers of UV across multiple scenarios. Under the weekend scenario, the Green Space Ratio (GSR) and the Vegetation Quality (VQ) notably enhanced the attractiveness of human activities. (4) The impacts of drivers varied at the urban, township, and street scales. The analysis focuses on factors with significant bandwidth changes across multiple scenarios: VQ, Remote-Sensing-based Ecological Index (RSEI), GSR, ASR, and ALSI. This study underscores the importance of socio-ecological land functions in enhancing urban vitality, offering valuable insights and data support for urban planning.

Keywords: urban vitality; socio-ecological land functions; human mobility intensity; multi-scale geographically weighted regression; spatial heterogeneity (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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